Application of an innovative narrow band vegetation index to corn leaves to explore the characteristics of corn spectra under Cu2+ stress
2022
Xia, Tian | Zhang, Chao | Yang, Keming | Fu, Pingjie | Wang, Min
In this study, an innovative narrow band vegetation index (INBVI) was proposed to explore the sensitive regions of corn leaves spectra under copper stress. In 2016, the spectra and Cu²⁺ contents of corn leaves under different copper stress concentrations were measured by designing corn stress experiments with different copper gradients. Firstly, we divided the spectra of corn leaves into 11 subintervals, and chose the spectral reflectance which corresponded to the middle wavelength of each subinterval to build INBVI. Then, the Pearson correlation coefficient (r) and Root Mean Square Error (RMSE) were calculated, and we analysed correlation of the INBVI and Cu²⁺ contents in corn leaves. What’s more, we compared it with the three conventional vegetation indexes of Water Band Index (WBI), Modified Chlorophyll Absorption Ratio Index (MCARI) and Normalized Difference Water Index (NDWI). Finally, the spectra of corn leaves obtained under the same experimental conditions in other year were used to verify the stability and effectiveness of INBVI. The results showed that the four subintervals of Green peak, Red edge, Near valley and Near peak A were sensitive intervals, because the absolute value of r exceeded .9, and the RMSE values were lower than other subintervals and the three conventional vegetation indexes. We verified the above results and found the sensitive intervals were Green peak, Red edge, Near valley and Near peak A, which were consistent with the sensitive subintervals obtained from the experiment data in 2016, and confirmed the effectiveness and stability of INBVI. The INBVI proposed in this paper can be used as a method to monitor copper pollution in corn leaves, and provide some theoretical support for the research of heavy metal pollution in other crops.
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